Further Topics in Spatial Econometrics

This chapter discusses some advanced special topics in spatial econometrics that have recently been introduced in the literature. The primary purpose is to make the reader knowledgeable on a set of techniques that represent the evolution of the methods presented in Chapter 3 and that constitute an essential part of the skill set currently required by spatial econometricians. These methods have the potential to make a tremendous impact in the analysis of real world problems in many scientific fields. In particular, section 4.1 discusses the case of non-constant innovation variances ( heteroscedastic models ), section 4.2 refers to the case where the dependent variable assumes a discrete (in particular, a binary) form, section 4.3 contains some of the modeling strategies in the field of diachronic spatial econometric models estimated on panel data and, finally, section 4.4 discusses regression models that are non-stationary in the geographical space. Following the introductory nature of the current presentation, we will discuss the various methods with less analytical detail compared to the rest of the book, while referring the interested reader to the current literature for more detail. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.